Mutational Landscape of Secondary Glioblastoma Guides MET-Targeted Trial in Brain Tumor.

Low-grade gliomas almost invariably progress into secondary glioblastoma (sGBM) with limited therapeutic option and poorly understood mechanism. By studying the mutational landscape of 188 sGBMs, we find significant enrichment of TP53 mutations, somatic hypermutation, MET-exon-14-skipping (METex14), PTPRZ1-MET (ZM) fusions, and MET amplification. Strikingly, METex14 frequently co-occurs with ZM fusion and is present in ∼14% of cases with significantly worse prognosis. Subsequent studies show that METex14 promotes glioma progression by prolonging MET activity. Furthermore, we describe a MET kinase inhibitor, PLB-1001, that demonstrates remarkable potency in selectively inhibiting MET-altered tumor cells in preclinical models. Importantly, this compound also shows blood-brain barrier permeability and is subsequently applied in a phase I clinical trial that enrolls MET-altered chemo-resistant glioma patients. Encouragingly, PLB-1001 achieves partial response in at least two advanced sGBM patients with rarely significant side effects, underscoring the clinical potential for precisely treating gliomas using this therapy.

Adaptive DNA amplification of synthetic gene circuit opens a way to overcome cancer chemoresistance.

Drug resistance continues to impede the success of cancer treatments, creating a need for experimental model systems that are broad, yet simple, to allow the identification of mechanisms and novel countermeasures applicable to many cancer types. To address these needs, we investigated a set of engineered mammalian cell lines with synthetic gene circuits integrated into their genome that evolved resistance to Puromycin. We identified DNA amplification as the mechanism underlying drug resistance in 4 out of 6 replicate populations. Triplex-forming oligonucleotide (TFO) treatment combined with Puromycin could efficiently suppress the growth of cell populations with DNA amplification. Similar observations in human cancer cell lines suggest that TFOs could be broadly applicable to mitigate drug resistance, one of the major difficulties in treating cancer.

Long-Term Succession Shows Interspecies Competition of Geobacter in Exoelectrogenic Biofilms.

Geobacter spp. are well-known exoelectrogenic microorganisms that often predominate acetate-fed biofilms in microbial fuel cells (MFCs) and other bioelectrochemical systems (BESs). By using an amplicon sequence variance analysis (at one nucleotide resolution), we observed a succession between two closely related species (98% similarity in 16S RNA), Geobacter sulfurreducens and Geobacter anodireducens, in the long-term studies (20 months) of MFC biofilms. Geobacter spp. predominated in the near-electrode portion of the biofilm, while the outer layer contained an abundance of aerobes, which may have helped to consume oxygen but reduced the relative abundance of Geobacter. Removal of the outer aerobes by norspermidine washing of biofilms revealed a transition from G. sulfurreducens to G. anodireducens. This succession was also found to occur rapidly in co-cultures in BES tests even in the absence of oxygen, suggesting that oxygen was not a critical factor. G. sulfurreducens likely dominated in early biofilms by its relatively larger cell size and production of extracellular polymeric substances (individual advantages), while G. anodireducens later predominated due to greater cell numbers (quantitative advantage). Our findings revealed the interspecies competition in the long-term evolution of Geobacter genus, providing microscopic insights into Geobacter's niche and competitiveness in complex electroactive microbial consortia.

Ionic Liquid Enriches the Antibiotic Resistome, Especially Efflux Pump Genes, Before Significantly Affecting Microbial Community Structure.

An expanding list of chemicals may permeabilize bacterial cells and facilitate horizontal gene transfer (HGT), which enhances propagation of antibiotic resistance genes (ARGs) in the environment. Previous studies showed that 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIm][PF6]), an ionic liquid, can facilitate HGT of some ARGs among bacteria. However, the dynamic response of a wider range of ARGs and associated mobile genetic elements (MGEs) in different environments is unknown. Here, we used metagenomic tools to study shifts of the resistome and microbiome in both sediments and freshwater microcosms exposed to [BMIm][PF6]. Exposure for 16 h to 0.1 or 1.0 g/L significantly enriched more than 207 ARG subtypes primarily encoding efflux pumps in freshwater microcosms as well as cultivable antibiotic-resistant bacteria. This resistome enrichment was attributed to HGT facilitated by MGEs (428 plasmids, 61 integron-integrase genes, and 45 gene cassettes were enriched) as well as to HGT-related functional genes. Interestingly, resistome enrichment occurred fast (within 16 h) after [BMIm][PF6] exposure, before any significant changes in bacterial community structure. Similar ARG enrichment occurred in sediment microcosms exposed to [BMIm][PF6] for 28 d, and this longer exposure affected the microbial community structure (e.g., Proteobacteria abundance increased significantly). Overall, this study suggests that [BMIm][PF6] releases could rapidly enrich the antibiotic resistome in receiving environments by increasing HGT and fortuitously selecting for efflux pump genes, thus contributing to ARG propagation.

Real-Time Imaging Revealed That Exoelectrogens from Wastewater Are Selected at the Center of a Gradient Electric Field.

Exoelectrogens acclimated from the environment are the key to energy recovery from waste in bioelectrochemical systems. However, it is still unknown how these bacteria are selectively enriched on the electrode. Here we confirmed for the first time that the electric field (EF) intensity selects exoelectrogens from wastewater using an integrated electrovisual system with a gradient EF. Under the operating conditions ( I = 3 × 10-3A), the EF intensity on the working electrode ranged from 6.00 V/cm at the center to 1.08 V/cm at the edge. A thick biofilm (88.9 µm) with spherical pink aggregates was observed at the center, while the color became gray at the edge (33.8 µm). The coverage of the biofilm also increased linearly with EF intensity from 0.42 at the edge (12 mm to the center) to 0.78 at the center. The biofilm at the center contained 76% Geobacter, which was 25% higher than that at the edge (60%). Geobacter anodireducens was the main species induced by the EF (50% at the center vs 24% at the edge). These results improve our fundamental knowledge of exoelectrogen acclimation and mixed electroactive biofilm formation, which has broader implications for energy recovery from waste and general understanding of microbial ecology.

Persistence of extracellular DNA in river sediment facilitates antibiotic resistance gene propagation.

The propagation of antibiotic resistance genes (ARGs) represents a global threat to both human health and food security. Assessment of ARG reservoirs and persistence is therefore critical for devising and evaluating strategies to mitigate ARG propagation. This study developed a novel, internal standard method to extract extracellular DNA (eDNA) and intracellular DNA (iDNA) from water and sediments, and applied it to determine the partitioning of ARGs in the Haihe River basin in China, which drains an area of intensive antibiotic use. The concentration of eDNA was higher than iDNA in sediment samples, likely due to the enhanced persistence of eDNA when associated with clay particles and organic matter. Concentrations of sul1, sul2, tetW, and tetT antibiotic resistance genes were significantly higher in sediment than in water, and were present at higher concentrations as eDNA than as iDNA in sediment. Whereas ARGs (frequently located on plasmid DNA) were detected for over 20 weeks, chromosomally encoded 16S rRNA genes were undetectable after 8 weeks, suggesting higher persistence of plasmid-borne ARGs in river sediment. Transformation of indigenous bacteria with added extracellular ARG (i.e., kanamycin resistance genes) was also observed. Therefore, this study shows that extracellular DNA in sediment is a major ARG reservoir that could facilitate antibiotic resistance propagation.

Genomic profiling and prognostic factors of H3 K27M-mutant spinal cord diffuse glioma.

H3 K27-altered diffuse midline glioma is a highly lethal pediatric-type tumor without efficacious treatments. Recent findings have highlighted the heterogeneity among diffuse midline gliomas with different locations and ages. Compared to tumors located in the brain stem and thalamus, the molecular and clinicopathological features of H3 K27-altered spinal cord glioma are still largely elusive, thus hindering the accurate management of patients. Here we aimed to characterize the clinicopathological and molecular features of H3 K27M-mutant spinal cord glioma in 77 consecutive cases. We found that the H3 K27M-mutant spinal cord glioma, with a median age of 35 years old, had a significantly better prognosis than H3 K27M-mutant brain tumors. We noticed a molecular heterogeneity of H3 K27M-mutant spinal cord astrocytoma via targeted sequencing with 34 cases. TP53 mutation which occurred in 58.8% of cases is mutually exclusive with PPM1D (26%) and NF1 (44%) mutations. The TP53-mutant cases had a significantly higher number of copy number variants (CNV) and a marginally higher proportion of pediatric patients (age at diagnosis <18 years old, p = 0.056). Cox regression and Kaplan-Meier curve analysis showed that the higher number of CNV events (≥3), chromosome (Chr) 9p deletion, Chr 10p deletion, ATRX mutation, CDK6 amplification, and retinoblastoma protein (RB) pathway alteration are associated with worse survival. Cox regression analysis with clinicopathological features showed that glioblastoma histological type and a high Ki-67 index (>10%) are associated with a worse prognosis. Interestingly, the histological type, an independent prognostic factor in multivariate Cox regression, can also stratify molecular features of H3 K27M-mutant spinal cord glioma, including the RB pathway, KRAS/PI3K pathway, and chromosome arms CNV. In conclusion, although all H3 K27M-mutant spinal cord diffuse glioma were diagnosed as WHO Grade 4, the histological type, molecular features representing chromatin instability, and molecular alterations associated with accelerated cell proliferative activity should not be ignored in clinical management.

scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors.

Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma.

BACKGROUND: Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. METHODS: We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. RESULTS: In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e-4 for progression-free survival (PFS) and 3.63e-4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher's exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e-4 for PFS and 3.66e-4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ). CONCLUSIONS: We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

Identifying predictors of glioma evolution from longitudinal sequencing.

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgram level, which are not avaiblable in certain situations like clinical biopsies or single-cell genomes. Here, we developed an alternative method-CNAPE to computationally infer copy number alterations from gene expression data. A prior knowledge-aided machine learning model was proposed, trained and tested on 9,740 cancer samples from The Cancer Genome Atlas. We then applied CNAPE to study gliomas, the most common and aggressive brain cancer in adult. Particularly, using RNA sequencing data, CNAPE respectively predicted DNA copy number of chromosomes, chromosomal arms, and 12 commonly altered genes, and achieved over 80 percent accuracy in almost all broad regions and some focal regions. CNAPE was developed as an easy-to-use tool at https://github.com/WangLabHKUST/CNAPE.

Metagenomic and bioanalytical insights into quorum sensing of methanogens in anaerobic digestion systems with or without the addition of conductive filter.

Understanding microbial interactions in the methanogenesis system through quorum sensing (QS) is very important for system optimization. Known QS genes were collected and classified into seven groups based on the signal molecules, which were used for constructing a hierarchical quorum sensing database (QSDB). QSDB containing 39,981 QS genes of seven QS groups was constructed and QS genes were analyzed with QSDB. Methanogen genomes were aligned with QSDB and acyl-homoserine lactones (AHLs) system was predicted as the most probable QS system. This database was further applied to analyze QS in methanogens from two upflow anaerobic sludge blanket-anaerobic filter hybrid reactors with conductive filter (CFB) and nonconductive filter (SEP), and a control without filter (CON). The maximum COD degradation rates in CFB (722.2 ± 10.1 mg/L·h) was elevated by 42.9% compared to CON (505.4 ± 5.98 mg/L·h). Metagenomic sequencing revealed Methanosaeta, Methanobacterium, and Methanosarcina were dominant, and the abundances was 4.3 times higher in the sludge of CFB compared to CON. The overall abundance of QS genes was CFB > SEP > CON, and AHLs were the most abundant group of QS genes. The filI/filR system, a luxI/luxR homolog, was firstly detected in methanogens, showing a high abundance in the CFB (0.085%) compared to in the CON (0.058%). The concentration of AHL molecules in CFB biofilms (0.04%) was about four times that in the CON (0.01%). Syntrophobacter and Smithella were the two major syntrophic bacteria of methanogens, and their abundances were positively correlated with methanogens. In addition, Syntrophobacter and Smithella harbored QS RpfB (component of the diffusible signal factor system) and PDE (component of cyclic di-GMP system). This study provides useful guidance for deeply understanding of QS in anaerobic digestion systems.

Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors.

Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and metastatic cancer cases, to assess metastatic risks of primary tumors. MetaNet achieves high accuracy in distinguishing the metastasis from the primary in breast and prostate cancers. From the prediction, we identify Metastasis-Featuring Primary (MFP) tumors, a subset of primary tumors with genomic features enriched in metastasis and demonstrate their higher metastatic risk and shorter disease-free survival. In addition, we identify genomic alterations associated with organ-specific metastases and employ them to stratify patients into various risk groups with propensities toward different metastatic organs. This organotropic stratification method achieves better prognostic value than the standard histological grading system in prostate cancer, especially in the identification of Bone-MFP and Liver-MFP subtypes, with potential in informing organ-specific examinations in follow-ups.

MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas.

Temozolomide (TMZ) is an oral alkylating agent used for the treatment of glioblastoma and is now becoming a chemotherapeutic option in patients diagnosed with high-risk low-grade gliomas. The O-6-methylguanine-DNA methyltransferase (MGMT) is responsible for the direct repair of the main TMZ-induced toxic DNA adduct, the O6-Methylguanine lesion. MGMT promoter hypermethylation is currently the only known biomarker for TMZ response in glioblastoma patients. Here we show that a subset of recurrent gliomas carries MGMT genomic rearrangements that lead to MGMT overexpression, independently from changes in its promoter methylation. By leveraging the CRISPR/Cas9 technology we generated some of these MGMT rearrangements in glioma cells and demonstrated that the MGMT genomic rearrangements contribute to TMZ resistance both in vitro and in vivo. Lastly, we showed that such fusions can be detected in tumor-derived exosomes and could potentially represent an early detection marker of tumor recurrence in a subset of patients treated with TMZ.

Deciphering Brain Complexity Using Single-cell Sequencing.

The human brain contains billions of highly differentiated and interconnected cells that form intricate neural networks and collectively control the physical activities and high-level cognitive functions, such as memory, decision-making, and social behavior. Big data is required to decipher the complexity of cell types, as well as connectivity and functions of the brain. The newly developed single-cell sequencing technology, which provides a comprehensive landscape of brain cell type diversity by profiling the transcriptome, genome, and/or epigenome of individual cells, has contributed substantially to revealing the complexity and dynamics of the brain and providing new insights into brain development and brain-related disorders. In this review, we first introduce the progresses in both experimental and computational methods of single-cell sequencing technology. Applications of single-cell sequencing-based technologies in brain research, including cell type classification, brain development, and brain disease mechanisms, are then elucidated by representative studies. Lastly, we provided our perspectives into the challenges and future developments in the field of single-cell sequencing. In summary, this mini review aims to provide an overview of how big data generated from single-cell sequencing have empowered the advancements in neuroscience and shed light on the complex problems in understanding brain functions and diseases.

RNA Exosome Complex-Mediated Control of Redox Status in Pluripotent Stem Cells.

The RNA exosome complex targets AU-rich element (ARE)-containing mRNAs in eukaryotic cells. We identified a transcription factor, ZSCAN10, which binds to the promoters of multiple RNA exosome complex subunits in pluripotent stem cells to maintain subunit gene expression. We discovered that induced pluripotent stem cell clones generated from aged tissue donors (A-iPSC) show poor expression of ZSCAN10, leading to poor RNA exosome complex expression, and a subsequent elevation in ARE-containing RNAs, including glutathione peroxidase 2 (Gpx2). Excess GPX2 leads to excess glutathione-mediated reactive oxygen species scavenging activity that blunts the DNA damage response and apoptosis. Expression of ZSCAN10 in A-iPSC recovers RNA exosome gene expression, the DNA damage response, and apoptosis. These findings reveal the central role of ZSCAN10 and the RNA exosome complex in maintaining pluripotent stem cell redox status to support a normal DNA damage response.

Enhanced horizontal transfer of antibiotic resistance genes in freshwater microcosms induced by an ionic liquid.

The spread and propagation of antibiotic resistance genes (ARGs) is a worldwide public health concern. Ionic liquids (ILs), considered as "environmentally friendly" replacements for industrial organic solvents, have been widely applied in modern industry. However, few data have been collected regarding the potential ecological and environmental risks of ILs, which are important for preparing for their potential discharge into the environment. In this paper, the IL 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIm][PF6]) (0.001-5.0 g/L) was tested for its effects on facilitating ARGs horizontal transfer mediated by plasmid RP4 in freshwater microcosms. In the horizontal transfer microcosms, the transfer frequency of plasmid RP4 was significantly enhanced (60-fold higher than untreated groups) by the IL [BMIm][PF6] (1.0 g/L). Meanwhile, two strains of opportunistic pathogen Acinetobacter spp. and Salmonella spp. were isolated among the transconjugants, illustrating plasmid RP4 mediated horizontal transfer of ARGs occurred in pathogen. This could increase the risk of ARGs dissemination to human pathogens and pose great threat to public health. The cause that [BMIm[PF6] enhanced the transfer frequency of plasmid RP4 was proposed by suppressed cell membrane barrier and enhanced cell membrane permeability, which was evidenced by flow cytometry (FCM). This is the first report that some ILs facilitate horizontal transfer of plasmid RP4 which is widely distributed in the environment and thus add the adverse effects of the environmental risk of ILs.

Fate and proliferation of typical antibiotic resistance genes in five full-scale pharmaceutical wastewater treatment plants.

This study investigated the characteristics of 10 subtypes of antibiotic resistance genes (ARGs) for sulfonamide, tetracycline, ß-lactam and macrolide resistance and the class 1 integrase gene (intI1). In total, these genes were monitored in 24 samples across each stage of five full-scale pharmaceutical wastewater treatment plants (PWWTPs) using qualitative and real-time quantitative polymerase chain reactions (PCRs). The levels of typical ARG subtypes in the final effluents ranged from (2.08±0.16)×10(3) to (3.68±0.27)×10(6) copies/mL. The absolute abundance of ARGs in effluents accounted for only 0.6%-59.8% of influents of the five PWWTPs, while the majority of the ARGs were transported to the dewatered sludge with concentrations from (9.38±0.73)×10(7) to (4.30±0.81)×10(10) copies/g dryweight (dw). The total loads of ARGs discharged through dewatered sludge was 7-308 folds higher than that in the raw influents and 16-638 folds higher than that in the final effluents. The proliferation of ARGs mainly occurs in the biological treatment processes, such as conventional activated sludge, cyclic activated sludge system (CASS) and membrane bio-reactor (MBR), implying that significant replication of certain subtypes of ARGs may be attributable to microbial growth. High concentrations of antibiotic residues (ranging from 0.14 to 92.2 mg/L) were detected in the influents of selected wastewater treatment systems and they still remain high residues in the effluents. Partial correlation analysis showed significant correlations between the antibiotic concentrations and the associated relative abundance of ARG subtypes in the effluent. Although correlation does not prove causation, this study demonstrates that in addition to bacterial growth, the high antibiotic residues within the pharmaceutical WWTPs may influence the proliferation and fate of the associated ARG subtypes.

Occurrence and distribution of sulfonamides, tetracyclines, quinolones, macrolides, and nitrofurans in livestock manure and amended soils of Northern China.

A feasible and rapid analysis for the simultaneous determination of sulfonamides (SAs), tetracyclines (TCs), fluoroquinolones (FQs), macrolides (MACs) and nitrofurans (NFs) in livestock manure and soils was established by solid-phase extraction (SPE)-ultra-performance liquid chromatography (UPLC)-tandem mass spectrometry (MS/MS). A total of 32 manure and 17 amended soil samples from the Liaoning and Tianjin areas in Northern China were collected for analysis. The largest detected frequencies and concentrations in manure samples were those of TCs (3326.6 ± 12,302.6 µg/kg), followed by FQs (411.3 ± 1453.4 µg/kg), SAs (170.6 ± 1060.2 µg/kg), NFs (85.1 ± 158.1 µg/kg), and MACs (1.4 ± 4.8 µg/kg). In general, veterinary antibiotics (VAs) were detected with higher concentrations in swine and chicken manure than in cattle manure, reflecting the heavy usage of VAs in swine and chicken husbandry in the studied area. Furthermore, higher residues of antibiotics were found in piglet and fattening swine manure than in sow manure. In addition, TCs were the most frequently (100%) detected antibiotics in amended soil with higher concentrations (up to 10,967.1 µg/kg) than any other VAs. The attenuation of SAs was more obvious than TCs in amended soil after fertilization, which can most likely be attributed to the stronger sorption of TCs than SAs to soil organic matter through cation exchange. This study illustrated the prevalence of TCs detected in both animal manure and fertilized agricultural soils in Northern China, which may increase the risk to human health through the food chain. Thus, TCs should be given more attention in the management of veterinary usage in livestock husbandry.

Occurrence of sulfonamide-, tetracycline-, plasmid-mediated quinolone- and macrolide-resistance genes in livestock feedlots in Northern China.

Antibiotic resistance genes (ARGs) in livestock feedlots deserve attention because they are prone to transfer to human pathogens and thus pose threats to human health. In this study, the occurrence of 21 ARGs, including tetracycline (tet)-, sulfonamide (sul)-, plasmid-mediated quinolone (PMQR)- and macrolide-resistance (erm) genes were investigated in feces and adjacent soils from chicken, swine, and cattle feedlots in Northern China. PMQR and sul ARGs were the most prevalent and account for over 90.0 % of the total ARGs in fecal samples. Specifically, PMQR genes were the most prevalent, accounting for 59.6 % of the total ARGs, followed by sul ARGs (34.2 %). The percentage of tet ARGs was 3.4 %, and erm ARGs accounted for only 1.9 %. Prevalence of PMQR and sul ARGs was also found in swine and cattle feces. The overall trend of ARG concentrations in feces of different feeding animals was chicken > swine > beef cattle in the studied area. In soils, sul ARGs had the highest concentration and account for 71.1 to 80.2 % of the total ARGs, which is possibly due to the widely distributed molecular carriers (i.e., class one integrons), facilitating sul ARG propagation. Overall, this study provides integrated profiles of various types of ARGs in livestock feedlots and thus provides a reference for the management of antibiotic use in livestock farming.